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The evolution of Robotics Technology has made the automatic application of sealants a reality and thus a necessity to maintain a competitive edge. Justification was made to design and install automated systems to account for nearly 70% of the sealing requirement for the General Motors new C/K Truck. A CAD/CAM simulation was completed generating an optimum robot layout as well as system design requirements. One of the innovations implemented as a part of this system was a robotically-applied cosmetic bead of sealant. To insure quality application to 100% of the truck box seams, techniques such as: analog sealant flow control, compliant sealant gun nozzles, and computer vision location of box corners were developed.

Robotic arc welding and plasma arc cutting, in general, require precise positioning of the torch relative to the workpiece. To this end, a 1-dimensional non-contact sensor was applied to two assembly plant tasks and found to perform to requirements while maintaining the system's cost effectiveness. This paper first presents a comparative overview of sensor technology typically used for arc welding. 1,2, and 3-D sensors are briefly compared in terms of functionality, operational complexity, and cost. Two plant applications are discussed to substantiate the conclusions. The first is an A-Pillar reinforcement MIG welding job. The second is a sunroof opening plasma cutting operation. This latter application requires part location in the absence of typical weld joints. In both instances, a robot mounted 1-D laser sensor was used to locate the part prior to the welding/cutting operation.

Machine vision technology is a tool being utilized in the new GMT-400 pickup truck Body Shops for process monitoring and control. These real-time Machine Vision Dimensional Gauging systems monitor 100% of the production's critical build features such as door and window openings, hinge locations, and fender mounting brackets, Traditional gauges typically can provide data on only a small sample of production −1% or less. Correlating the machine vision systems to master gauges allows accurate data to be collected on every job as it is being built. This complete dimensional control data provides information for process monitoring as well as a means to detect tooling adjustment requirements and the ability to detect build problems, even if they occur intermittently. Several methods of performing this correlation have been investigated, with the goal being to define a correlation procedure that works well in the plant environment.